Mutual Successive Interference Cancellation Strategies in NOMA for Enhancing the Spectral Efficiency of CoMP Systems

International audienceThe densification of mobile networks should enable the fifth generation (5G) mobile networks to cope with the ever increasing demand for higher rate traffic, reduced latency, and improved reliability. The large scale deployment of small cells and distributed antenna systems in heterogeneous environments will require more elaborate interference mitigating techniques to increase spectral efficiency and to help unlock the expected performance leaps from the new network topologies. Coordinated multi-point (CoMP) is the most advanced framework for interference management enabling the cooperation between base stations to mitigate inter-cell interference and boost cell-edge user performance. In this paper, we study the combination of CoMP with mutual SIC, an interference cancellation technique based on power-domain non-orthogonal multiple access (NOMA) that enables multiplexed users to simultaneously cancel their corresponding interfering signals. A highly efficient inter-cell interference cancellation scheme is then devised, that can encompass several deployment configurations and coordination techniques. The obtained results prove the superiority of this approach compared to conventional NOMA-CoMP systems

Achievable rates of iterative MIMO receivers over interference channels

In this thesis, we study the achievable rates of some interference communication schemes when iterative interference-cancellation (IC) is applied. We assume multiple-input multiple-output (MIMO) communication employing iterative receivers with linear front-ends which involves two modules concatenated serially and cooperating iteratively; a linear combiner based on minimum-mean-square-error (MMSE) detection or maximal-ratio-combining (MRC) and a SISO decoder. We investigate the achievable rates of this receiver when the transmitted signal is Gaussian-distributed with hypothetical erasure-type feedback from the decoder to the combiner and a more practical case with large-size QAM constellations with log-likelihood-ratios (LLRs) being exchanged between the receiver's modules. The achievable rate is approximated by the area below the EXIT curve of the linear FE receiver. Some properties have been observed and mathematically been proved about the iterative MIMO receivers with linear front-end

On Efficient Signal Processing Algorithms for Signal Detection and PAPR Reduction in OFDM Systems

The driving force of the study is susceptibility of LS algorithm to noise. As LS algorithm is simple to implement, hence it’s performance improvement can contribute a lot to the wireless technology that are especially deals with high computation. Cascading of AdaBoost algorithm with LS greatly influences the OFDM system performance. Performance of Adaptive Boosting based symbol recovery was investigated on the performance of LS, MMSE, BLUE were also compared with the performance of AdaBoost algorithm and MMSE has been found the higher computational complexity. Furthermore, MMSE also requires apriori channel statistics and computational complexity O(5N3) of the MMSE increases exponentially as the number of carrier increases. For the Adaboost case the computational complexity calculation is little different.Therefore, in the training stage of the AdaBoost algorithm, the computational complexity is only O(nT M) Furthermore, as it is a classification algorithm so in the receiver side we will require a separate de-mapper (or decoder) to get the desired data bits, i.e., a. SAS aided DCT based PAPR reduction 1326 and b. SAS aided DCT based PAPR reduction. A successive addition subtraction preprocessed DCT based PAPR reduction technique was proposed. Here, the performance of proposed method was compared with other preexisting techniques like SLM and PTS and the performance of the proposed method was seen to outperform specially in low PAPR region. In the proposed PAPR reduction method, the receiver is aware of the transmitted signal processing, this enables a reverse operation at the receiver to extract the transmit data. Hence the requirement of sending extra information through extra subcarrier is eliminated. The proposed method is also seen to be spectrally efficient. In the case of PTS and SLM it is inevitable to send the side information to retrieve the transmit signal. Hence, these two methods are spectrally inefficient. Successive addition subtraction based PAPR reduction method was also applied to MIMO systems. The performance of the SAS based PAPR reduction method also showed better performance as compared to other technique. An extensive simulation of MIMO OFDM PAPR reduction was carried out by varying the number of subcarriers and number of transmitter antennas. A detailed computational complexity analysis was also carried out. BATE aided SDMA multi user detection. A detailed study of SDMA system was carried out with it’s mathematical analysis.Many linear and non linear detectors like ML, MMSE, PIC, SIC have been proposed in literature for multiuser detection of SDMA system. However, except MMSE every receivers other are computational extensive. So as to enhance the performance of the MMSE MUD a meta heuristic Bat algorithm was incorporated in cascade with MMSE

Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey

Integrated sensing and communication (ISAC) has the advantages of efficient spectrum utilization and low hardware cost. It is promising to be implemented in the fifth-generation-advanced (5G-A) and sixth-generation (6G) mobile communication systems, having the potential to be applied in intelligent applications requiring both communication and high-accurate sensing capabilities. As the fundamental technology of ISAC, ISAC signal directly impacts the performance of sensing and communication. This article systematically reviews the literature on ISAC signals from the perspective of mobile communication systems, including ISAC signal design, ISAC signal processing algorithms and ISAC signal optimization. We first review the ISAC signal design based on 5G, 5G-A and 6G mobile communication systems. Then, radar signal processing methods are reviewed for ISAC signals, mainly including the channel information matrix method, spectrum lines estimator method and super resolution method. In terms of signal optimization, we summarize peak-to-average power ratio (PAPR) optimization, interference management, and adaptive signal optimization for ISAC signals. This article may provide the guidelines for the research of ISAC signals in 5G-A and 6G mobile communication systems.Comment: 25 pages, 13 figures, 8 tables. IEEE Internet of Things Journal, 202

Iterative Receiver Techniques for Data-Driven Channel Estimation and Interference Mitigation in Wireless Communications

Wireless mobile communications were initially a way for people to communicate through low data rate voice call connections. As data enabled devices allow users the ability to do much more with their mobile devices, so to will the demand for more reliable and pervasive wireless data. This is being addressed by so-called 4th generation wireless systems based on orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) antenna systems. Mobile wireless customers are becoming more demanding and expecting to have a great user experience over high speed broadband access at any time and anywhere, both indoor and outdoor. However, these promising improvements cannot be realized without an e±cient design of the receiver. Recently, receivers utilizing iterative detection and decoding have changed the fundamental receiver design paradigm from traditional separated parameter estimation and data detection blocks to an integrated iterative parameter estimator and data detection unit. Motivated by this iterative data driven approach, we develop low complexity iterative receivers with improved sensitivity compared to the conventional receivers, this brings potential benefits for the wireless communication system, such as improving the overall system throughput, increasing the macro cell coverage, and reducing the cost of the equipments in both the base station and mobile terminal. It is a challenge to design receivers that have good performance in a highly dynamic mobile wireless environment. One of the challenges is to minimize overhead reference signal energy (preamble, pilot symbols) without compromising the performance. We investigate this problem, and develop an iterative receiver with enhanced data-driven channel estimation. We discuss practical realizations of the iterative receiver for SISO-OFDM system. We utilize the channel estimation from soft decoded data (the a priori information) through frequency-domain combining and time-domain combining strategies in parallel with limited pilot signals. We analyze the performance and complexity of the iterative receiver, and show that the receiver's sensitivity can be improved even with this low complexity solution. Hence, seamless communications can be achieved with better macro cell coverage and mobility without compromising the overall system performance. Another challenge is that a massive amount of interference caused by MIMO transmission (spatial multiplexing MIMO) reduces the performance of the channel estimation, and further degrades data detection performance. We extend the iterative channel estimation from SISO systems to MIMO systems, and work with linear detection methods to perform joint interference mitigation and channel estimation. We further show the robustness of the iterative receivers in both indoor and outdoor environment compared to the conventional receiver approach. Finally, we develop low complexity iterative spatial multiplexed MIMO receivers for nonlinear methods based on two known techniques, that is, the Sphere Decoder (SD) method and the Markov Chain Monte Carlo (MCMC) method. These methods have superior performance, however, they typically demand a substantial increase in computational complexity, which is not favorable in practical realizations. We investigate and show for the first time how to utilize the a priori information in these methods to achieve performance enhancement while simultaneously substantially reducing the computational complexity. In our modified sphere decoder method, we introduce a new accumulated a priori metric in the tree node enumeration process. We show how we can improve the performance by obtaining the reliable tree node candidate from the joint Maximum Likelihood (ML) metric and an approximated a priori metric. We also show how we can improve the convergence speed of the sphere decoder (i.e., reduce the com- plexity) by selecting the node with the highest a priori probability as the starting node in the enumeration process. In our modified MCMC method, the a priori information is utilized for the firrst time to qualify the reliably decoded bits from the entire signal space. Two new robust MCMC methods are developed to deal with the unreliable bits by using the reliably decoded bit information to cancel the interference that they generate. We show through complexity analysis and performance comparison that these new techniques have improved performance compared to the conventional approaches, and further complexity reduction can be obtained with the assistance of the a priori information. Therefore, the complexity and performance tradeoff of these nonlinear methods can be optimized for practical realizations

Performance analysis of diversity techniques for OFDM and base station cooperation

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2010.Thesis (Master's) -- Bilkent University, 2010.Includes bibliographical references leaves 76-80.The main goal of the next generation wireless communication systems is to provide high data rate services. In order to deal with performance-limiting challenges that include frequency selective fading channels, power and bandwidth constraints, multiple input multiple output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques have been proposed as effective techniques to combat fading and to provide high rate reliable transmission. In this thesis we first give an overview of WiMAX as an example of an OFDM system and study the performance of the WiMAX physical layer under different MIMO techniques. We also analyze space-frequency coding and propose a threaded algebraic space-time (TAST) based code. Secondly, since the mobile bandwidth is an expensive and scarce resource, it seems likely that a high frequency reuse will be employed in the future cellular networks to increase spectral efficiency. This means that base stations (BSs) will operate in the same frequency band and therefore cause cochannel interference (CCI) to the users at other cells. CCI is an important performance degrading factor. Therefore our second aim is to investigate BS cooperation techniques to mitigate CCI. We assume that channel state information (CSI) is available at the cooperating BSs and analyze the performance gains due to cooperation when used in conjunction with Alamouti space-time coding.Üzeler, HandeM.S

Code-aided iterative techniques in OFDM systems

Inspired by the 'turbo principle', this thesis deals with two iterative technologies in orthogonal frequency division multiplexing (OFDM) systems: iterative interference cancelation in space-frequency block coded OFDM (SFBC-OFDM) and iterative channel estimation/ tracking in OFDM Access (OFDMA) with particular application to Worldwide Inter-operability for Microwave Access (WiMAX) systems. The linear matched filter (MF) decoding in SFBC-OFDM is simple yet obtains maximumlikelihood (ML) performance based on the assumption that the channel frequency response remains constant within a block. However, frequency response variations gives rise to inter-channel interference (lCI). In this thesis, a parallel interference cancelation (PIC) approach with soft iterations will be proposed to iteratively eliminate ICI in G4 SFBC-OFDM. Furthermore, the information from outer convolutional decoder is exploited and fed back to aid the inner PIC process to generate more accurate coded bits for the convolutional decoder. Therefore, inner and outer iterations work in a collaborative way to enhance the performance of interference cancelation. Code-aided iterative channel estimation/tracking has the ability of efficiently improving the quality of estimation/tracking without using additional pilots/training symbols. This technique is particularly applied to OFDMA physical layer ofWiMAX systems according to the Institute of Electrical and Electronics Engineers (IEEE) 802.16 standard. It will be demonstrated that the performance of the pilot-based channel estimation in uplink (UL) transmission and the channel tracking based on the preamble symbol in downlink (DL) transmission can be improved by iterating between the estimator and the detector the useful information from the outer convolutional codes. The above two issues will be discussed in Chapter 5 and Chapter 6, and before this, Chapter 2 to Chapter 4 will introduce some background techniques that are used throughout the thesis

Index modulation for next generation wireless communications.

Doctoral Degree. University of KwaZulu-Natal, Durban.A multicarrier index modulation technique in the form of quadrature spatial modulation (QSM) orthogonal frequency division multiplexing (QSM-OFDM) is proposed, in which transmit antenna indices are employed to transmit additional bits. Monte Carlo simulation results demonstrates a 5 dB gain in signal-to-noise ratio (SNR) over other OFDM schemes. Furthermore, an analysis of the receiver computational complexity is presented. A low-complexity near-ML detector for space-time block coded (STBC) spatial modulation (STBC-SM) with cyclic structure (STBC-CSM), which demonstrate near-ML error performance and yields significant reduction in computational complexity is proposed. In addition, the union-bound theoretical framework to quantify the average bit-error probability (ABEP) of STBC-CSM is formulated and validates the Monte Carlo simulation results. The application of media-based modulation (MBM), to STBC-SM and STBC-CSM employing radio frequency (RF) mirrors, in the form of MBSTBC-SM and MBSTBC-CSM is proposed to improve the error performance. Numerical results of the proposed schemes demonstrate significant improvement in error performance when compared with STBC-CSM and STBC-SM. In addition, the analytical framework of the union-bound on the ABEP of MBSTBC-SM and MBSTBC-CSM for the ML detector is formulated and agrees well with Monte Carlo simulations. Furthermore, a low-complexity near-ML detector for MBSTBC-SM and MBSTBC-CSM is proposed, and achieves a near-ML error performance. Monte Carlo simulation results demonstrate a trade-off between the error performance and the resolution of the detector that is employed. Finally, the application of MBM, an index modulated system to spatial modulation, in the form of spatial MBM (SMBM) is investigated. SMBM employs RF mirrors located around the transmit antenna units to create distinct channel paths to the receiver. This thesis presents an easy to evaluate theoretical bound for the error performance of SMBM, which is validated by Monte Carlo simulation results. Lastly, two low-complexity suboptimal mirror activation pattern (MAP) optimization techniques are proposed, which improve the error performance of SMBM significantly

Interference mitigation using group decoding in multiantenna systems

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